|Publication number||US7515305 B2|
|Application number||US 11/084,280|
|Publication date||Apr 7, 2009|
|Filing date||Mar 18, 2005|
|Priority date||Mar 18, 2005|
|Also published as||US20060209101|
|Publication number||084280, 11084280, US 7515305 B2, US 7515305B2, US-B2-7515305, US7515305 B2, US7515305B2|
|Original Assignee||Xerox Corporation|
|Export Citation||BiBTeX, EndNote, RefMan|
|Patent Citations (6), Referenced by (21), Classifications (14), Legal Events (3)|
|External Links: USPTO, USPTO Assignment, Espacenet|
The exemplary embodiments relate to the art of digital imaging. It finds particular application in macro uniformity corrections for non-uniformities in a raster output scanning (ROS) printing system and will be described with particular reference thereto. It will be appreciated, however, that the disclosure is also amenable to other like applications.
Macro non-uniformity levels have existed in raster scan image output terminals (IOTs) (e.g., xerographic printers) for some time and are a concern for most marking processes. Even small non-uniformity level errors in raster scan IOTs give rise to visually objectionable banding in halftone outputs (e.g., image macro non-uniformity streak artifacts). Such errors typically arise in raster scan image output terminals (IOTs) due to variations in ROS spot size across the field (which is constant in time (print to print)), donor-roll once-around, HSD wire hysteresis, laser diode variations, LED bar power variation, ROS scan line non-uniformity, photoreceptor belt sensitivity variations, and/or ROS velocity non-uniformity. Significantly, many variations occur only in the fast scan (e.g., X) or slow scan (e.g., Y) directions, and they do not interact to first order. Therefore, a correction made in one direction has a negligible effect on artifacts in the other direction. Other printing technologies (e.g. thermal inkjet and acoustical ink printing) also have artifacts that occur in a regular, predictable manner in one or both directions and fall within the scope of this discussion.
Although techniques have been proposed to eliminate such non-uniformity errors by making physical systems more uniform, it is too expensive to control or limit the error to an acceptable level, below which the error will not be detected by the unaided eye. Fixes have been attempted in the marking process, but not enough latitude exists to fully solve the problem. For problem sources such as LED non-uniformity, the correction is sometimes addressed with current control or pulse width control. However, none of the solutions discussed above implements a technique based in digital electronics. With the cost of computing rapidly decreasing, such digital electronics based solutions are becoming more attractive.
The exemplary embodiments provide a new and improved method which overcomes the above-referenced problems and others. The exemplary embodiments relate to a method for sensing print defects in electrostatically formed images. It is to be appreciated that the exemplary embodiments are also amenable to other like applications.
Various apparatuses for recording images on sheets have heretofore been put into practical use. When the subsystems of an electrophotographic or similar image forming system operate under suboptimal conditions, a lack of print uniformity may result. Streaks can arise from a non-uniform LED imager, contamination of the high voltage elements in a charger, scratches in the photoreceptor surface, etc.
In a uniform patch of gray, streaks and bands may appear as a variation in the gray level. In general, “gray” refers to the intensity value of any single color separation layer, whether the toner is black, cyan, magenta, yellow, or some other color. One method of reducing such streaks is to design and manufacture the critical parameters of the marking engine subsystems to tight specifications. Often though, such precision manufacturing will prove to be cost prohibitive.
The streaks that can arise from the different subsystems can be prevented by modifying the image or actuating another subsystem to counteract the streak. To counteract streaks that arise, their size and magnitude must be sensed and measured with high precision. One of the image quality attributes of high quality printers is spatial uniformity in the cross process direction. In order to monitor the spatial uniformity, an accurate image processing technique is required to measure the uniformity. The image processing algorithms heretofore known, for detecting or sensing defects, fail or give erroneous results. Making high precision measurements of the streak's magnitude and size is limited by distortions that occur during the printing of the image and/or scanning of the image. The distortions may not be objectionable in viewing typical images, but they may be of a magnitude that prevents an accurate measurement of the degree of streaking. Examples of printing and/or scanning defects include process and cross process position waviness, image rotation, process direction expansion of the image, image deletions, background toner, and scanner induced distortion of the image.
A tone reproduction curve (TRC) may be measured by printing patches of different bitmap area coverage. In some digital image processing applications, the reflectivity of a patch of gray is measured with a toner area coverage sensor. The manner of operation of the fixed position sensor is described in U.S. Pat. No. 4,553,033, which is incorporated herein by reference in its entirety. Toner area coverage sensors are typically designed with an illumination beam much larger than the halftone screen dimension. This large beam does not provide the resolution for the toner area coverage sensor to be useful as a sensor for the narrow streaks that may occur for poorly performing subsystems.
U.S. Pat. No. 6,760,056 by Klassen et. al, incorporated herein by reference in its entirety, discloses one exemplary embodiment of a method for compensating for streaks introducing a separate tone reproduction curve for each pixel column in the cross process direction. A compensation pattern is printed and then scanned to first measure the ideal tone reproduction curve and then detects and measure streaks. The tone reproduction curves for the pixel columns associated with the streak are then modified to compensate for the streak.
The subject application is related to the following co-pending application: U.S. application Ser. No. 10/739,177, filed Dec. 19, 2003, by Howard Mizes, entitled “Systems and Methods for Compensating For Streaks in Images”, which is herein incorporated by reference.
According to one aspect, a xerographic device utilizing a method is provided for measuring spatial uniformity in an image. The method comprises printing a test pattern from an image forming device including a plurality of strips and rows of fiducials proximal thereto. The method further provides for correcting of distortions in an image caused by printing and scanning artifacts and mapping from scanner coordinates to digital image coordinates. A gray level of each strip in the plurality of strips can be determined as a function of digital image cross process coordinate. A profile of each strip can be filtered whereby the artifacts from a halftone screen are eliminated.
According to another aspect, a printing system utilizing a method is provided for measuring spatial uniformity in an image that is translated through an image forming device. The method comprises printing a test pattern from the image forming device including a plurality of strips in a process direction. The test pattern can include a series of fiducials aligned in rows in the process direction. Each row of fiducials can be proximal to a separate one of the plurality of strips. A process direction displacement can be determined as a function of a cross process position of the first strip of the test pattern. Each pixel column of an image can be shifted in the process direction to adjust the first strip in a horizontal orientation. A location of the first strip can be identified from the plurality of strips and a first row of fiducials adjacent thereto. A scanner cross process position of each fiducial is determined in the first row of fiducials, wherein the scanner cross process position coordinates can be mapped to digital image cross process position coordinates.
According to yet another aspect, a method is provided for measuring spatial uniformity in an image that is translated through an image forming device. The method comprises printing a test pattern from the image forming device including a top line and a plurality of strips below the top line in a process direction. The test pattern can include a series of fiducials aligned in rows in the process direction. Each row of fiducials can be adjacent to a separate one of the plurality of strips. The method further includes determining a process direction displacement as a function of a cross process position of the top line of the test pattern and extracting a profile of the top line. Each pixel column of the image is shifted in the process direction to adjust the top line in a horizontal orientation. The location of a first strip is identified from the plurality of strips and a first row of fiducials adjacent thereto. A scanner cross process position coordinate of each fiducial is determined in the first row of fiducials.
According to yet still a further aspect, a method is provided for measuring print uniformity in an image that is translated through an image forming device, including printing a test pattern from the image forming device having a strip. A cross section of the strip is measured for determining a dot and space periodicity pattern from a halftone brick of the strip. The measuring of the cross section includes printing a test pattern from the image forming device including a solid top line and a plurality of strips below the top line in a process direction. The test pattern includes a series of fiducials aligned in rows in the process direction. Each row of fiducials can be adjacent to a separate one of the plurality of strips. A process direction displacement is then determined as a function of a cross process position of the top line of the test pattern. A profile of the top line is extracted. Each pixel column of the image is shifted in the process direction to adjust the top line in a horizontal orientation. The method further provides for identifying the location of a first strip from the plurality of strips and a first row of fiducials adjacent thereto, and descreening the halftone brick to remove the periodicity.
While the method to process scanned images for uniformity will hereinafter be described in connection with exemplary embodiments, it will be understood that it is not intended to limit the embodiments. On the contrary, it is intended to cover all alternatives, modifications and equivalents as may be included within the spirit and scope of the embodiments as defined by the appended claims.
Turning now to
The print engine 26 is beneficially an electrophotographic engine; however, it will become evident from the following discussion that the exemplary embodiments are useful in a wide variety of digital copying and printing machines and are not limited in its application to the printing machine shown herein. The print engine 26 is illustrated as incorporating a raster output scanner (ROS) lens system 32 and three (3) array systems 34, 36, 38 for producing color. The engine 26, which operates on the print ready binary data from the IPS 22 to generate a color document in a single pass, selectively charges a photoreceptive surface in the form of a photoreceptor belt 30. Briefly, the uniformly charged photoreceptor 30 is initially exposed to a light image which represents a first color image separation, such as black, at the ROS 32. The resulting electrostatic latent image is then developed with black toner particles to produce a black toner image. This same image area with its black toner layer is then recharged, exposed to a light image which represents a second color separation such as yellow at the array lens 34, and developed to produce a second color toner layer. This recharge, expose, and develop image on image (REaD lol) process may be repeated at the array lens 36, and the array lens 38 to subsequently develop image layers of different colors, such as magenta and cyan.
The methods, to be described in detail below, describe a series of image processing algorithms that allow a print uniformity to be sensed or monitored in the presence of scanning and printing defects or profile artifacts. Accurate image processing methods enable the print or spatial uniformity to be sensed and measured. One such method includes printing a test or compensation pattern from which the uniformity can be measured. The test pattern can be scanned on an image capture device, such as, for example, a flatbed scanner, that has process control marks and/or alignment marks (i.e. fiducials) before and/or after a halftone strip that extends across a process direction. The alignment marks provide alignment between a printer pixel grid and a scanning pixel grid. From this test pattern, and the associated printing defects, print uniformity can be monitored and sensed through the series of image processing algorithms.
Referring now to
Referring now to
While making reference to the test pattern of
If the uniformity across the full printable area is needed, it may not be possible to print the side fiducials 72, 73, 74, . . . 79, and 82, 83, 84, . . . 89 at the left and right side of the test pattern 48. Alternatively then, for dark strips, for example 52, 53, 54, 55, one can use the strip itself to identify the top and bottom boundaries. For light strips, for example 56, 57, 58, 59, the presence of any sort of noise may cause errors in locating the position of the strips. Under these conditions, the position of the row of fiducials 66, 67, 68, 69 in the process direction can be used to estimate the position of the strips 56, 57, 58, 59. Specifically, the periodic pattern of the fiducials can be used to identify them with high precision. A single scan line in the cross process direction that runs through the fiducials will show a periodic response at the period of the fiducials and a Fourier Transform at this frequency will be large. A scan line running through the paper or through the strip will not have this periodicity. Therefore, a plot of the amplitude at this periodic frequency, as a function of scan line, will have a series of peaks at the positions of the fiducials. The positions of the strips 52, 53, 54, . . . 59 can then be inferred from the positions of the fiducials 62, 63, 64, . . . 69.
In steps 600 and 700, the cross process position of each fiducial in the row of fiducials below the current strip is determined. The technique to do this identification in the presence of noise is described hereinafter and shown in more detail in the flowchart of
In step 800, a mapping or calibration function that translates or generates the cross process position in the digital image to the cross process position in the scanned image is determined. The mapping function is a plot of the position of the fiducials in the digital image to the position of the fiducials in the scanned image. Linear interpolation can be utilized between measured points to give a continuous calibration curve.
In step 900, the strip profile is determined. For each cross process digital image pixel column, the corresponding cross process position is determined for the scanned image. The sum over the strip width for the pixel column to the left and to the right of the cross process position is determined. Linear interpolation between these two sums is performed based on how far the corresponding cross process position is between the two pixel columns.
If this is the last strip of the image, then the algorithm is finished and the profile of each strip is returned. However, if this is not the last strip, the rotation of the current row of fiducials can be determined. If the only distortions of the image shown in
Referring again to
Referring again to
The index of the pulse positions are identified by finding all the local minimums of this profile in step 605. The local minimum exists below some threshold (to distinguish it from noise due to paper fibers). Because of background toner t such as illustrated in
Because of deletions d as illustrated in
Because of compression or expansion of the image (refer to
A high resolution descreening technique can be employed to make high resolution corrections to the image.
Descreening is the name of a technique to remove the cross section periodicity. Descreening algorithms can be used in input scanners where the halftone of the printed image is not desired in the color scan. The way descreening typically works is to perform an average of the input pixels over an area the size of the halftone dot spacing. However, an algorithm performed in this way will blur the image. For bitmap compensation of streaks, blurring of the image is undesirable. If the blurring of the image is too severe, the compensation will not be able to compensate for the sharp edges in a uniformity profile as well as extremely narrow streaks.
The exemplary embodiments take a different approach to descreening. The cross section of the strip can be thought of as a halftone structure superimposed upon the true nonuniformity across the strip. The periodicity of the halftone in the cross section is equal to the dimension of the halftone brick in the cross process direction. The strips are long, so the halftone repeats many times across the cross section. To extract a halftone contribution to the cross section, the gray level for the same pixel in the halftone brick can be averaged across the whole cross section. To be specific, assume the halftone brick is 10 pixels long. Therefore, we calculate 10 numbers. The first is the average of the gray level at indices 1, 11, 21, 31, . . . in the cross section. The second is the average of the gray level at indices 2, 12, 22, 32, . . . in the cross section. The last is the average of the gray levels at indices 10, 20, 30, 40, . . . in the cross section.
The streaks in the image arising from the subsystems should be uncorrelated with the halftone. Therefore, the gray level when averaged over every 10th index should tend to be independent of the nonuniformity. What is left over then is the contribution of the halftone. Once the halftone contribution is determined, it is subtracted from the signal, leaving only the true nonuniformity signal. This algorithm is shown graphically in
Alternatively, another method to exclude the halftone contribution to the cross process uniformity is to apply a series of notch filters. A notch filter attenuates frequencies in the vicinity of a chosen frequency (the notch) and passes other frequencies. A series of notch filters will attenuate all frequencies at the frequency of the notches. The frequency of the halftone in the cross process direction can be determined from the digital image or from the Fourier transform of a typical profile of a uniform strip. There may be more than one frequency at which the halftone repeats. Techniques well known in the field of signal processing can be used to define a notch filter or a series of notch filters that eliminates the halftone frequencies but passes other frequencies. A kernel is a profile in real space derived from the notch filter that when convoluted with the signal will result in a filtered cross process uniformity profile that does not contain the contribution from the halftone at the halftone repeat frequency. If there is more than one halftone repeat frequency, the kernels from the series of notch filters can be applied in sequence. Suboptimal application of the notch filters could result in profile artifacts. These might include a phase shift of the signal, which would shift the detected position of a streak in the cross process direction. These might also include edge effects, where artificial oscillations and/or noise are introduced at the edge of the profile. These might still also include artificial periodic oscillations at the cutoff frequencies of the notch filter. Techniques known in the field of signal processing can be applied to minimize these artifacts.
Still another method to exclude the halftone contribution to the cross process uniformity is to apply a low pass filter. A low pass filter attenuates frequencies above a chosen frequency and passes frequencies below a chosen frequency. The frequency of the halftone in the cross process direction can be determined from the digital image or from the Fourier transform of a typical profile of a uniform strip. There may be more than one frequency at which the halftone repeats. Techniques well known in the field of signal processing can be used to define a low pass filter that eliminates frequencies at and above the halftone frequencies but passes other frequencies. A kernel is a profile in real space derived from the low pass filter that when convoluted with the signal will result in a filtered cross process uniformity profile that does not contain the contribution from the halftone at the halftone repeat frequency. Suboptimal application of the low pass filters could result in profile artifacts. These might include a phase shift of the signal, which would shift the detected position of a streak in the cross process direction. These might also include edge effects, where artificial oscillations and/or noise are introduced at the edge of the profile. These might still also include artificial periodic oscillations at the cutoff frequencies of the low pass filter. Techniques known in the field of signal processing can be applied to minimize these artifacts.
It will be appreciated that various of the above-disclosed and other features and functions, or alternatives thereof, may be desirably combined into many other different systems or applications. Also that various presently unforeseen or unanticipated alternatives, modifications, variations or improvements therein may be subsequently made by those skilled in the art which are also intended to be encompassed by the following claims.
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|U.S. Classification||358/3.26, 358/3.06, 358/504, 358/406|
|International Classification||G06K15/00, H04N1/405, H04N1/407, H04N1/46, G06T5/00, H04N1/409|
|Cooperative Classification||H04N1/506, B41J29/393|
|European Classification||H04N1/50D, B41J29/393|
|Mar 18, 2005||AS||Assignment|
Owner name: XEROX CORPORATION, CONNECTICUT
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:MIZES, HOWARD;REEL/FRAME:016399/0245
Effective date: 20041215
|Jun 30, 2005||AS||Assignment|
Owner name: JP MORGAN CHASE BANK, TEXAS
Free format text: SECURITY AGREEMENT;ASSIGNOR:XEROX CORPORATION;REEL/FRAME:016761/0158
Effective date: 20030625
Owner name: JP MORGAN CHASE BANK,TEXAS
Free format text: SECURITY AGREEMENT;ASSIGNOR:XEROX CORPORATION;REEL/FRAME:016761/0158
Effective date: 20030625
|Sep 17, 2012||FPAY||Fee payment|
Year of fee payment: 4